import streamlit as st
from transformers import pipeline

rewriter = pipeline("text2text-generation", model='google/flan-t5-large')
classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-es-en")
translator_arabe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ar")
translator_french = pipeline("translation", model="Helsinki-NLP/opus-mt-en-fr")
tone_classifier = pipeline("zero-shot-classification", model="roberta-large-mnli")



text1 = st.text_area('Enter your text for the first exercise')

text2 = st.text_area('Enter your text for the second exercise')

if text1:

    text_translate = translator(text1)[0]['translation_text']
    
    prompt = f"""
    Rewrite the following technical text in common language\n
    Texto: "{text_translate}"
    """
    
    out = rewriter(prompt,max_length=400, num_return_sequences=1, do_sample=True, temperature=0.7, top_p=0.9, repetition_penalty=1.1)
    st.write("Text in Common Lenguage:")
    st.json(out)

    text_response = out[0]['generated_text']

    prompt = f"""
    Identify the main theme of the text\n
    Texto: "{text_response}"
    """
    theme_labels = ["biology", "genetics", "technology", "engineering", "medicine"]
    theme_result = classifier(text_response, candidate_labels=theme_labels)
    st.write("Main Theme:")
    st.json(theme_result)

    out_arabe = translator_arabe(text_response)
    st.write("Translation to Arabic:")
    st.json(out_arabe)

    out_french = translator_french(text_response)
    st.write("Translation to French:")
    st.json(out_french)

    prompt = f"""
    Identify the tone in which the text is written\n
    Text: "{text_response}"
    """
    
    tone_labels = ["neutral", "formal", "informal"]
    tone_result = tone_classifier(text_response, candidate_labels=tone_labels)
    st.write("Tone:")
    st.json(tone_result)
    

if text2:
    text_translate = translator(text2)[0]['translation_text']
    
    prompt = f"""
    From this information, infer two possible conclusions explained in a way that a 10-year-old child can understand.\n
    Text: "{text_translate}"
    """

    out = rewriter(prompt,max_length=400, num_return_sequences=1, do_sample=True, temperature=0.7, top_p=0.9, repetition_penalty=1.1)
    st.write("Conclusions Infered:")
    st.json(out)

    prompt = f"""
    Suggests two areas of future research related to these results.
    Text: "{out[0]['generated_text']}"
    """

    out = rewriter(prompt,max_length=400, num_return_sequences=1, do_sample=True, temperature=0.7, top_p=0.9, repetition_penalty=1.1)
    st.write("Areas of future research:")
    st.json(out)